How to Operate PV-Driven Residential Heat Pumps Under Time-Varying Tariffs

Why It Matters

The model offers a practical pathway for households in tariff‑responsive markets to cut heating costs while reliably maintaining comfort, accelerating the shift toward electrified heating and behind‑the‑meter renewables.

Key Takeaways

• Robust scheduling cuts heat‑pump electricity bills under dynamic tariffs.
• PV integration adds low‑cost energy, boosting load‑shifting flexibility.
• PMV comfort model yields lower costs than temperature‑band constraints.
• Chance‑constrained framework guarantees comfort despite PV forecast errors.
• Approach adaptable to markets, but requires local calibration.

Pulse Analysis

Electrified heating is reshaping residential energy demand, especially in Europe where time‑varying electricity tariffs are becoming commonplace. Homeowners with rooftop solar face a dual challenge: they must balance the intermittent nature of PV generation against the need to keep indoor temperatures comfortable. Traditional control strategies rely on fixed price signals and simple temperature bounds, often missing cost‑saving opportunities when cheap, renewable energy is available. The new scheduling model addresses this gap by treating tariff timing, PV output, and building thermal inertia as simultaneous decision variables, enabling heat pumps to pre‑heat or maintain comfort during low‑price or high‑PV periods.

At the core of the approach is distributionally robust chance‑constrained programming, which safeguards comfort even when PV forecast errors deviate from assumed distributions. By integrating a DOE‑ANOVA framework, the researchers quantify how PV uncertainty, tariff structure, and comfort definitions interact. The study contrasts indoor‑temperature (IT) constraints with a predicted mean vote (PMV) comfort metric; the latter, by reflecting occupant perception rather than strict temperature limits, expands the feasible operating region and consistently lowers electricity costs. Although the PMV‑based strategy can slightly reduce the heat pump’s coefficient of performance, the overall cost benefit outweighs the modest efficiency trade‑off.

For utilities and policymakers, the findings highlight the economic upside of dynamic pricing combined with behind‑the‑meter solar. Households can achieve meaningful bill reductions without compromising comfort, provided they adopt robust, data‑driven scheduling tools. However, successful deployment demands local calibration of tariff profiles, climate data, and heat‑pump performance curves. As more regions adopt variable tariffs and encourage residential solar, such adaptable optimization frameworks will be essential for unlocking the full potential of low‑carbon, cost‑effective heating solutions.